Add @spaces.GPU decorators to Gradio wrapper functions

- Decorate gradio_initialize() with @spaces.GPU(duration=120)
- Decorate gradio_estimate() with @spaces.GPU(duration=30)
- Remove @spaces.GPU from class methods to avoid double decoration
- ZeroGPU requires decorators on functions directly connected to Gradio

This fixes: 'No @spaces.GPU function detected during startup'

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

app.py

@@ -38,7 +38,6 @@ class FoundationPoseInference:
         self.tracked_objects = {}
         self.use_real_model = USE_REAL_MODEL
 
-    @spaces.GPU(duration=120)  # Allocate GPU for 120 seconds (includes model loading)
     def initialize_model(self):
         """Initialize the FoundationPose model on GPU."""
         if self.initialized:
@@ -112,7 +111,6 @@ class FoundationPoseInference:
             logger.info(f"✓ Object '{object_id}' registered (placeholder mode)")
             return True
 
-    @spaces.GPU(duration=10)
     def estimate_pose(
         self,
         object_id: str,
@@ -265,6 +263,7 @@ async def api_estimate(request: EstimateRequest):
 
 
 # Gradio wrapper functions
+@spaces.GPU(duration=120)
 def gradio_initialize(object_id: str, reference_files: List, fx: float, fy: float, cx: float, cy: float):
     """Gradio wrapper for object initialization."""
     try:
@@ -291,7 +290,7 @@ def gradio_initialize(object_id: str, reference_files: List, fx: float, fy: floa
             "cy": cy
         }
 
-        # Register object (calls @spaces.GPU decorated method)
+        # Register object
         success = pose_estimator.register_object(
             object_id=object_id,
             reference_images=reference_images,
@@ -308,6 +307,7 @@ def gradio_initialize(object_id: str, reference_files: List, fx: float, fy: floa
         return f"Error: {str(e)}"
 
 
+@spaces.GPU(duration=30)
 def gradio_estimate(object_id: str, query_image: np.ndarray, fx: float, fy: float, cx: float, cy: float):
     """Gradio wrapper for pose estimation."""
     try:
@@ -322,7 +322,7 @@ def gradio_estimate(object_id: str, query_image: np.ndarray, fx: float, fy: floa
             "cy": cy
         }
 
-        # Estimate pose (calls @spaces.GPU decorated method)
+        # Estimate pose
         result = pose_estimator.estimate_pose(
             object_id=object_id,
             query_image=query_image,